Evidence map›Paper›PMID 30212456›Full record

ArticlePloS one2018

Detection of genetic alterations in gastric cancer patients from Saudi Arabia using comparative genomic hybridization (CGH).

Fehmida Bibi, Isse Ali, Muhammad Imran Naseer, Hussein Sheikh Ali Mohamoud, Muhammad Yasir, Sana Akhtar Alvi, Asif Ahmed Jiman-Fatani, Ali Sawan, Esam Ibraheem Azhar

Abstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Review
  6. Article
  7. Multifaceted Role of PRDM Proteins in Human Cancer.International journal of molecular sciences · 2020
    Review
  8. Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Fehmida BibiSpecial Infectious Agents Unit, King Fahd Medical Research Centre, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia.ORCID 0000-0002-5178-1471
Isse AliCentre for Computational Intelligence (CCI), Faculty of Technology, De Montfort University, United Kingdom.
Muhammad Imran NaseerCenter of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, Saudi Arabia.
Hussein Sheikh Ali MohamoudDepartment of Clinical Genetics, St George's University Hospitals NHS Foundation Trust, Cranmer Terrace London, United Kingdom.
Muhammad YasirSpecial Infectious Agents Unit, King Fahd Medical Research Centre, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia.
Sana Akhtar AlviSpecial Infectious Agents Unit, King Fahd Medical Research Centre, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia.
Asif Ahmed Jiman-FataniDepartment of Medical Microbiology and Parasitology, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.
Ali SawanDepartment of Anatomical Pathology, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.
Esam Ibraheem AzharSpecial Infectious Agents Unit, King Fahd Medical Research Centre, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe present study was conducted to discover genetic imbalances such as DNA copy number variations (CNVs) associated with gastric cancer (GC) and to examine their association with different genes involved in the process of gastric carcinogenesis in Saudi population.

methodsFormalin-fixed paraffin-embedded (FFPE) tissues samples from 33 gastric cancer patients and 15 normal gastric samples were collected. Early and late stages GC samples were genotyped and CNVs were assessed by using Illumina HumanOmni1-Quad v.1.0 BeadChip.

resultsCopy number gains were more frequent than losses throughout all GC samples compared to normal tissue samples. The mean number of the altered chromosome per case was 64 for gains and 40 for losses, and the median aberration length was 679115bp for gains and 375889bp for losses. We identified 7 high copy gain, 52 gains, 14 losses, 32 homozygous losses, and 10 copy neutral LOHs (loss of heterozygosities). Copy number gains were frequently detected at 1p36.32, 1q12, 1q22, 2p11.1, 4q23-q25, 5p12-p11, 6p21.33, 9q12-q21.11, 12q11-q12, 14q32.33, 16p13.3, 17p13.1, 17q25.3, 19q13.32, and losses at 1p36.23, 1p36.32, 1p32.1, 1q44, 3q25.2, 6p22.1, 6p21.33, 8p11.22, 10q22.1, 12p11.22, 14q32.12 and 16q24.2. We also identified 2 monosomy at chromosome 14 and 22, 52 partially trisomy and 22 whole chromosome 4 neutral loss of heterozygosities at 13q14.2-q21.33, 5p15.2-p15.1, 5q11.2-q13.2, 5q33.1-q34 and 3p14.2-q13.12. Furthermore, 11 gains and 2 losses at 1p36.32 were detected for 11 different GC samples and this region has not been reported before in other populations. Statistical analysis confirms significant association of H. pylori infection with T4 stage of GC as compare to control and other stages.

conclusionsWe found that high frequency of copy number gains and losses at 1p36.23, 1p32.1, 1p36.32, 3q25.2, 6p21.33 and 16q24.2 may be common events in gastric cancer. While novel CNVs at 1p36.32 harbouring PRDM16, TP73 and TP73-AS1 genes showed 11 gains and 2 losses for 11 different GC cases and this region is not reported yet in Database of Genomic Variants may be specific to Saudi population.

Indexed as

Chromosome AberrationsPolymorphism, Single NucleotideAdultAgedAged, 80 and overCase-Control StudiesComparative Genomic HybridizationDNA Copy Number VariationsFemaleGene Regulatory NetworksHelicobacter InfectionsHumansLoss of HeterozygosityMaleMiddle AgedNeoplasm Staging

Identifiers

PMID30212456
PMCPMC6136709

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.